AI Build Engineer

Job Summary

We are seeking a skilled and experienced AI Build Engineer to join our dynamic team. This role will be responsible for building and deploying cutting-edge AI solutions, leveraging a variety of technologies and methodologies. The ideal candidate will possess a strong foundation in software engineering principles and a passion for AI innovation.

Key Responsibilities

The AI Build Engineer will be responsible for the design, development, and implementation of AI applications. This includes collaborating with cross-functional teams to define requirements, designing and building robust and scalable AI solutions, and ensuring the quality and reliability of deployed AI models. The role also involves continuous monitoring and optimization of AI systems to ensure peak performance and alignment with business objectives.

Required Skills & Qualifications

• Programming Languages: Proficiency in multiple programming languages including Python, JavaScript, TypeScript, and C#. This includes the ability to write clean, efficient, and well-documented code.
• Large Language Models (LLMs): A strong understanding of LLMs and their application in various use cases.
• Retrieval-Augmented Generation (RAG): Experience with RAG techniques to enhance the capabilities of LLMs.
• Prompt Engineering: Expertise in Prompt Engineering to design effective prompts for LLMs.
• Vector Databases: Familiarity with Vector Databases and their use in storing and retrieving vector embeddings.
• Agentic AI: Knowledge of Agentic AI principles and their application in building autonomous agents.
• Cloud Platforms: Experience with cloud platforms such as Azure and AWS, including Azure AI Services, Azure OpenAI, AWS Bedrock, and Vertex AI.
• Containerization & Orchestration: Proficiency in Docker and Kubernetes for containerizing and orchestrating AI applications.
• DevOps & CI/CD: Experience with DevOps practices and CI/CD pipelines using tools like GitHub Actions and Azure DevOps.
• MLOps: Understanding of MLOps principles and best practices for managing the ML lifecycle.
• AI Application Integration: Ability to integrate AI applications into existing systems and workflows.
• Testing & Monitoring: Experience with AI-infused testing, Monitoring, and Observability tools and techniques.
• Governance: Understanding of Governance principles related to AI systems.
• API & Microservices: Experience with API development and Microservices architectures.
• Additional Skills: Familiarity with MCP, Playwright, and AI copilots.

Qualifications: Possession of AI/Cloud certifications such as Azure AI Engineer or AWS ML is highly desirable.

Experience Required: We are seeking candidates with 5-10 years of relevant experience in software engineering and AI development. This level of experience should demonstrate a proven ability to design, build, and deploy complex AI solutions in a production environment.

What We Offer

The role is onsite.